@qhdrl12
基本信息
MCP server for AI image generation and editing using Google's Gemini Flash models. Create images from text prompts with intelligent filename generation and strict text exclusion. Supports text-to-image generation with future expansion to image editing capabilities.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-gemini-image-generator": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@qhdrl12/mcp-server-gemini-image-gen",
"--client",
"claude"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
This MCP server enables AI assistants to generate high-quality images from text prompts and transform existing images using Google's Gemini model via the MCP protocol. It handles prompt engineering, text-to-image conversion, intelligent filename generation, and local image storage. Aimed at users of MCP-compatible clients such as Claude Desktop, Cursor, or other hosts.
Install via Smithery (npx -y @smithery/cli install @qhdrl12/mcp-server-gemini-image-gen --client claude), or manually clone the repo, create a Python 3.11+ virtual environment, and install dependencies. Configure a Gemini API key (via Google AI Studio) and an optional image output path. Add the server to your MCP client’s configuration (e.g., claude_desktop_config.json) with the command, args, and env keys. Invoke the three available MCP tools: generate_image_from_text, transform_image_from_encoded, or transform_image_from_file.
It provides text-to-image and image-to-image transformation specifically via Google’s Gemini Flash model, with dual return (image bytes and saved file path). It also offers automatic non-English prompt translation and strict text exclusion from generated images.
Python 3.11 or higher, a Google AI API key (Gemini), and an MCP-compatible host application (e.g., Claude Desktop, Cursor).
Images are saved to a local directory specified by the `OUTPUT_IMAGE_PATH` environment variable. The server also returns raw image data (bytes) for direct use.
When used with Claude Desktop Host, `transform_image_from_encoded` may perform slowly due to large base64 data transfer, and path resolution problems can occur with returned file paths. Using alternative MCP clients or the `transform_image_from_file` method is recommended.
Authentication requires a Google AI API key, set via the `GEMINI_API_KEY` environment variable in the MCP client configuration or a `.env` file. The API key provides a certain free quota per month.
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